From 66adb952847fe1a91a2e7bc081591e5304b82053 Mon Sep 17 00:00:00 2001
From: Ashley Xu <139821907+ashleyxuu@users.noreply.github.com>
Date: Fri, 2 Feb 2024 10:26:44 -0800
Subject: [PATCH] docs: BigQuery Vector Search went public review and updated
 docs (#16896)

Update the docs for BigQuery Vector Search
---
 docs/docs/integrations/platforms/google.mdx          |  6 +-----
 .../vectorstores/bigquery_vector_search.ipynb        | 12 +-----------
 2 files changed, 2 insertions(+), 16 deletions(-)

diff --git a/docs/docs/integrations/platforms/google.mdx b/docs/docs/integrations/platforms/google.mdx
index 5d09b18f56b..b1ab193a80a 100644
--- a/docs/docs/integrations/platforms/google.mdx
+++ b/docs/docs/integrations/platforms/google.mdx
@@ -207,15 +207,11 @@ from langchain_community.vectorstores import MatchingEngine
 > [Google BigQuery](https://cloud.google.com/bigquery),
 > BigQuery is a serverless and cost-effective enterprise data warehouse in Google Cloud.
 >
-> Google BigQuery Vector Search
+> [Google BigQuery Vector Search](https://cloud.google.com/bigquery/docs/vector-search-intro)
 > BigQuery vector search lets you use GoogleSQL to do semantic search, using vector indexes for fast but approximate results, or using brute force for exact results.
 
 > It can calculate Euclidean or Cosine distance. With LangChain, we default to use Euclidean distance.
 
-> This is a private preview (experimental) feature. Please submit this
-> [enrollment form](https://docs.google.com/forms/d/18yndSb4dTf2H0orqA9N7NAchQEDQekwWiD5jYfEkGWk/viewform?edit_requested=true)
-> if you want to enroll BigQuery Vector Search Experimental.
-
 We need to install several python packages.
 
 ```bash
diff --git a/docs/docs/integrations/vectorstores/bigquery_vector_search.ipynb b/docs/docs/integrations/vectorstores/bigquery_vector_search.ipynb
index af26dcaf8e0..403a8d9fbd2 100644
--- a/docs/docs/integrations/vectorstores/bigquery_vector_search.ipynb
+++ b/docs/docs/integrations/vectorstores/bigquery_vector_search.ipynb
@@ -7,22 +7,12 @@
    },
    "source": [
     "# BigQuery Vector Search\n",
-    "> **BigQueryVectorSearch**:\n",
-    "BigQuery vector search lets you use GoogleSQL to do semantic search, using vector indexes for fast approximate results, or using brute force for exact results.\n",
+    "> [**BigQuery Vector Search**](https://cloud.google.com/bigquery/docs/vector-search-intro) lets you use GoogleSQL to do semantic search, using vector indexes for fast approximate results, or using brute force for exact results.\n",
     "\n",
     "\n",
     "This tutorial illustrates how to work with an end-to-end data and embedding management system in LangChain, and provide scalable semantic search in BigQuery."
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This is a **private preview (experimental)** feature. Please submit this\n",
-    "[enrollment form](https://docs.google.com/forms/d/18yndSb4dTf2H0orqA9N7NAchQEDQekwWiD5jYfEkGWk/viewform?edit_requested=true)\n",
-    "if you want to enroll BigQuery Vector Search Experimental."
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {